AbstractCellular
Manufacturing (CM), which contains the flexibility of Job-Shop and
at the same time has a higher rate of production as flow lines, is
proving to be a useful substitute for the production carried out in
batches. In spite of the fact that there are so many benefits
associated with CM but designing CM, for real world problems, is a
very complex job. Since the main task in designing a CM is grouping
of machines into cells and parts into corresponding families,
therefore, most of the research carried out so far has considered
the Cellular Manufacturing System (CMS) design as a Machine-Part
grouping problem only and focus on the operational aspects of the
design has been very little. Once the Machine-Part grouping stage is
over, scheduling of the system is supposed to be the next stage in
completing the operational design of a CMS. This is the stage where
important production related information; such as processing
sequence and processing time is taken into consideration. Scheduling
is very essential as it enhances productivity and maximizes the
usefulness of a given manufacturing system by utilizing the
available resources in an optimized manner. Therefore, alongside
Machine-Part grouping, scheduling is of paramount importance too, as
it ensures proper utilization of resources.
In order to carryout a complete operational design of CMS, a two
stage methodology has been developed in this research. First, the
problem of Machine-Part grouping (CMS design) is solved, and then
sequencing and scheduling of parts on machines is carried out. Since
each cell is like a Job-Shop, therefore the scheduling part of the
problem is solved using a similar approach as in case of a Job-Shop
scheduling problem (JSSP).
Separate hybrid tools, for solving Machine-Part grouping problem and
Job-Shop Scheduling Problem (JSSP), has been developed by combining
Genetic Algorithms (GA) with Local Search Heuristics (LSH). Each
tool’s effectiveness has been verified, separately, by solving a
number of benchmark problems from literature. Finally, the two tools
are combined in such a manner that the output of the Machine-Part
grouping serves as an input to the tool developed for the scheduling
of Job-Shop. Final outcome of the program is a cellular arrangement
of the system (machine groups and corresponding part families) and
detailed information about the sequencing and scheduling of the
system.
The development of two effective hybrid GA based tools, for
Machine-Part grouping and Job-Shop Scheduling, and their combination
are the main contributions of this research..